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<div class="title">Bayesian Network [![Build Status](<a href="https://travis-ci.org/godai0519/BayesianNetwork.svg?branch=master">https://travis-ci.org/godai0519/BayesianNetwork.svg?branch=master</a>)](<a href="https://travis-ci.org/godai0519/BayesianNetwork">https://travis-ci.org/godai0519/BayesianNetwork</a>) </div>  </div>
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<div class="textblock"><h2>What's this</h2>
<p>This software is for Bayesian Network (BN) Library. <br />
A implementation of Bayesian Networks Model for pure C++11, included Loopy-BP and Likelihood Weighting. <br />
Development is not yet finished, but you can already use.</p>
<p>このソフトウェアはベイジアンネットワークのためのライブラリです． <br />
C++14を使用して実装しており，Loopy-BPやLikelihood Weighingといったベイジアンネットワークモデルを提供します．</p>
<h2>Install</h2>
<p>This library is implemented as Header Only Library. <br />
Just through the <code>/path/to/BayesianNetwork</code> directory. (ex. <code>-I/path/to/BayesianNetwork</code>)</p>
<p>header onlyライブラリとして実装してあるので，ディレクトリへのパスを通すだけで使用可能です． <br />
(ex. <code>-I/path/to/BayesianNetwork</code>)</p>
<h2>Compilers Tested</h2>
<ul>
<li>Linux:<ul>
<li>GCC, C++11: 4.8.1, 4.9.2, 5.0.0</li>
<li>Clang, C++11: 3.5, 3.7.0 (trunk)</li>
</ul>
</li>
<li>Windows:<ul>
<li>Visual C++: 12.0 (CTP_Nov2013), 13.0</li>
</ul>
</li>
</ul>
<h2>Feature</h2>
<h3>Bayesian Network structure learning</h3>
<ul>
<li>Brute Force class<ul>
<li>search all patterns, very very slow.</li>
</ul>
</li>
<li>Greedy class<ul>
<li>some patterns(not become good score) ignore, fast a little.</li>
</ul>
</li>
<li>Simulated Annealing class<ul>
<li>as if a metal, with spending time, structure is less likely to change.</li>
</ul>
</li>
<li>K2 Algorithm class<ul>
<li>give information that you already know some relations between nodes.</li>
</ul>
</li>
<li>Stepwise Structure<ul>
<li>first, make some cluster that include some node, one after another cluster combine two clusters.</li>
</ul>
</li>
</ul>
<h5>Available Algorithms in Stepwise Structure</h5>
<table class="markdownTable">
<tr class="markdownTableHead">
<th class="markdownTableHeadRight"></th><th class="markdownTableHeadCenter">Learning in Cluster  </th><th class="markdownTableHeadCenter">Learning between Cluster   </th></tr>
<tr class="markdownTableBody" class="markdownTableRowOdd">
<td class="markdownTableBodyRight">Brute Force  </td><td class="markdownTableBodyCenter">OK  </td><td class="markdownTableBodyCenter">OK   </td></tr>
<tr class="markdownTableBody" class="markdownTableRowEven">
<td class="markdownTableBodyRight">Greedy  </td><td class="markdownTableBodyCenter">OK  </td><td class="markdownTableBodyCenter">OK   </td></tr>
<tr class="markdownTableBody" class="markdownTableRowOdd">
<td class="markdownTableBodyRight">Simulated Annealing  </td><td class="markdownTableBodyCenter">OK  </td><td class="markdownTableBodyCenter"><em>NG</em>   </td></tr>
<tr class="markdownTableBody" class="markdownTableRowEven">
<td class="markdownTableBodyRight">K2 Algorithm  </td><td class="markdownTableBodyCenter">OK  </td><td class="markdownTableBodyCenter"><em>NG</em>   </td></tr>
</table>
<h3>Inferring unobserved variables</h3>
<ul>
<li>Loopy-BP class<ul>
<li>high-speed and strong in a loop graph.</li>
</ul>
</li>
<li>Rejection Sampling (a.k.a. Logic Sampling) class<ul>
<li>very simple, but very slowly.</li>
</ul>
</li>
<li>Likelihood Weighting<ul>
<li>higher than Rejection Sampling, and extremely accuracy.</li>
</ul>
</li>
</ul>
<h2>Author and Contact</h2>
<p>Feel free to contact me ;) <br />
Bugs and issues are reportable below:</p><ul>
<li><a href="//github.com/godai0519/BayesianNetwork/issues">GitHub Issue</a></li>
<li><a href="//twitter.com/godai_0519">Twitter</a></li>
<li><a href="//www.facebook.com/godai.azuma">Facebook</a></li>
<li><a href="//d.hatena.ne.jp/godai_0519/">Blog</a></li>
</ul>
<h2>Licence</h2>
<p>Code released under <a href="//github.com/godai0519/BayesianNetwork/blob/master/LICENSE">the MIT license</a>. </p>
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